A study of in situ degradability: heterogeneity of variances and correlated errors

Scientia Agricola

Taciana Villela Savian²  Joel Augusto Muniz¹ 

[1] ,Programa de Pós-Graduação em Agronomia/Estatística e Experimentação Agropecuária

关键词: ruminal degradability;    non-linear regression;    parameters estimation;    coast-cross grass;    degradabilidade ruminal;    regressão não-linear;    estimação de parâmetros;    gramínea coast-cross;   

DOI  :  10.1590/S0103-90162007000500013

来源: SciELO

【 摘 要 】

Degradation models exhibit a non-linear behavior and the selection of a model to describe the degradability depends on the coherence of the model with the involved biological events. The purpose of this study is to evaluate the behavior of the parameters of the degradation model proposed by Mertens & Loften, adjusted to the results of an in situ degradability trial. The experiment evaluated the potential degradable residue of neutral detergent fiber (NDF) of coastcross grass (Cynodon dactylon × Cynodon nlemfuensis) submitted to two cutting ages (30 and 90 days), with three replicates. For each cutting age, the potentially degradable residue of NDF was studied using fifteen incubation times (0; 0,5; 1; 3; 6; 9; 12; 18; 34; 35; 48; 56; 72; 96 e 120 hours). The experimental unit comprised one non-lactating cow with a permanent ruminal fistula. Mean and individual adjustments were obtained for the animals in three different configurations: inverse variance weight without autoregressive errors; unweighted with autoregressive errors, and unweighted without autoregressive errors. Variances of parameter estimators were also obtained by means of the mean parameter covariance matrix, providing expressions for the estimation of the confidence age for the parameters of the model. A weighting of the model by the inverse variance resulted in estimates statistically equal to zero for the colonization time. The use of a structure of second order autoregressive errors improved the fit of the model of Mertens & Loften, providing more precise estimates of the parameters.

【 授权许可】

CC BY   
 All the contents of this journal, except where otherwise noted, is licensed under a Creative Commons Attribution License